FIG. 17 is a block diagram showing an arrangement of a digital color image processing system. FIG. 18 is a block diagram showing an arrangement of a conventional edge processing circuit. FIGS. 19(a)-(c) are block diagrams showing an arrangement of a hue detect circuit and related tables. FIGS. 20(a) through (c) are a graph and explanatory diagrams, which are useful in explaining a character spread phenomenon. FIGS. 21(a) through (c) are explanatory diagrams for explaining edge emphasis processing.
Generally, a color copying machine exercises a developing process of Y (yellow), M (magenta), C (cyan), and K (black), to reproduce a full color image of a color original. To store full color image data gathered by a single scan of a color image of an original, a considerably large memory capacity is required. To avoid this, in the conventional developing process, the machine scans the color original separately for each color, and executes signal processing.
In image reading, a line sensor optically reads an image to gather image data in terms of color separated signals of B (blue), G (green), and R (red). The separated color signals, as shown in FIG. 17, pass through an END converter 501 and a color masking (color correction) 502, and are transformed into color toner signals Y, M and C. Then, the toner signals enter a UCR 503. In the UCR, the black (K) generation and the under color removal are carried out. The toner signal as generally designated by X passes through a hue separation type non-linear filter section, TRC (tone adjustment) 510, and SG (screen generator) 511, and is converted into binary data. The binary signal is used to control a laser beam that expose a photosensitive member. The images of the respective colors are superposed by the mesh-dot gradation, to reproduce the full color image.
In the images handled by a digital color image processing system, a binary image, such as characters and lines, and a halftone image, such as photographs and mesh-dot printing materials, usually coexist. To obtain a binary image of high sharpness, the original image containing such different images is subjected to edge emphasis processing, which is based on non-linear filter processing. As regards the edge emphasis processing, there have been many proposals. One of those proposals is the arrangement of FIG. 17, which is provided with a hue separation type non-linear filter section.
The filter section, as shown, receives the image data signal X of a developing color as selected from Y, M, C, and signals according to the developing process. The toner signals are generated through black generation and under color removal processing. The image data signal X is branched into two routes. The data signal X flowing through one of the routes enters a smoothing filter 504 where it is smoothed. The data signal X is also edge emphasized by the combination of a "r (gamma)" conversion 506, an edge detect filter 507, and an edge emphasizing LUT 508. The data signals from the two routes are added together by an adder 509, which in turn produces a non-linear filter signal. An arrangement of the edge emphasis processing circuit is shown in FIG. 18.
In edge processing, the hue detect circuit 505 detects the hue of an input image, and determines whether the developing color at that time is a necessary color or an unnecessary color. If the input image is a black area, the chromatic signals of Y, M, and C are not edge emphasized, but only the color signal of K is emphasized according to an edge quantity.
As shown in FIG. 19(a), the hue detect circuit 505 is made up of a max./min. circuit 512 for obtaining the maximum and minimum values of the toner signals Y, M, and C, a multiplexer 513 for selecting a developing color, a subtractor 514 for calculating a difference between the maximum and minimum values, another subtractor 515 for calculating a difference between the minimum value and a developing color, and comparators 516 to 518, which compare input signals with threshold values. When the input signals are larger than the threshold values, the comparators produce signals r, m, c', m', an y' with logic value "1".
The hue detect circuit recognizes a hue by using a hue decision table as shown in FIG. 19(b). Further, it determines whether the developing color is a necessary color of logic "1" or an unnecessary color of logic "0" by using a necessary/unnecessary color decision table shown in FIG. 19(c). The hues that are output as the result of the hue determination, are eight colors, (white), Y, M, C, B, G, R, and K, that are used as normal character colors.
As seen from the hue decision table, if the hue is B, the necessary developing colors "m" and "c", and the remaining developing colors are unnecessary. In this case, during a necessary color cycle, the edges of the signal are emphasized by the LUT (1) of the edge emphasis LUT 508. During an unnecessary color cycle, the edges are not emphasized by the LUT (2) of the LUT 508.
As described above, in edge emphasis processing, the hue of the input signal is discriminated by comparing the input signal with the threshold value "th." Depending on the comparison result, an edge detect signal is converted, by the edge emphasis LUT, into an edge emphasis signal. Meanwhile, the MTF (modulation transfer function) characteristic of the IIT (image input terminal) becomes poor as frequency becomes high, as shown in FIG. 20(a). The degree of degradation of the MTF also changes depending on the color and the main and vertical scan directions. When the MTF is degraded, an optical density distribution curve on "a" an original is flattened to be a curve "b" (see FIG. 20(b)). In detecting a hue, the signal "b" is compared with the threshold value "th," and the hue is determined on the basis of the comparison result. Accordingly, the signal whose hue is recognized has a width w', which is much wider than the width "w" of the original signal. This defines a range of the edge emphasis processing. On the basis of the determination result, an edge emphasis signal "d" as shown in FIG. 20(c) is added to it, to emphasize the edges. Consequently, it is reproduced in the form of a widened character as indicated by "c" in FIG. 20(b). The character widening is caused not only by the IIT, but also by developing material, developing method, developing characteristic and the like.
When compared to the conventional edge emphasis system in which the color signals of Y, M, C, and K are all subjected to the edge emphasis processing, the edge emphasis system as mentioned above improves the reproduction quality of a black character, but the smoothing signals are left in the Y, M, and C signals. As indicated by the edge emphasis LUT 508 shown in FIG. 18, the necessary color is emphasized by the LUT (1), while the unnecessary color is removed by the LUT (2). Accordingly, an edge emphasis processing signal is generated that does not emphasize the colors of Y, M, and C of a filter input signal of a black character (as shown in FIG. 21(a)) does emphasize only the black signal K. In the smoothing filter, a smoothing processing signal resulting from smoothing all of the color signals Y, M, C, and K is generated, as shown in FIG. 21(b). When finally composed the smoothing signal of Y, M, C, and K is as shown in FIG. 21(c).
Usually, even in the case of the black character, the signal contains not only the K signal but also the Y, M, and C signals. The smoothed colors of Y, M, and C appear at the edge portions. Thus, the black character cannot be reproduced by a single color of K. In connection with the case of the single color reproduction, the instant case suffers from color change and a loss of color purity, which are due to widening of lines, impaired registration, and the like. The resultant image will not be sharp.
In case where there are originals containing binary images, such as characters and lines, and halftone images, such as photographs and mesh-dot printing materials, and the type of the image can be designated for each original or each area, it is possible to select optimum parameters for the respective types of images. In the case of an image of the type in which the binary image and the halftone image coexist (this type of the image will be referred to as an integrated image original), the parameters selected are those allowing both types of images to be reproduced. Accordingly, the binary image and the halftone image cannot be individually processed in the best conditions, and hence satisfactory images are hard to obtain. In the case of the binary image, the edge emphasis is weak, and the sharpness of the characters is lost. In the case of a black character, the edge portions and small characters are blurred. In the case of the halftone image, the frequencies near the edge detect frequency ar emphasized. This impairs the smoothness of the halftone image, and causes unpleasant Moire to appear in the image. Additionally the edges are unnaturally emphasized. Thus, the resultant image looks hard and rough.